Combined impact of semantic segmentation and quantitative structure modelling of Southern pine trees using terrestrial laser scanning by Jinyi Xia, Timothy A. Martin, Gary F. Peter, Kody M. Brock, Jeff W. Atkins, Matthew A. Gitzendanner, Inacio Bueno, Kim Calders, Ana Paula Dalla Corte, Andrew T. Hudak, Monique Bohora Schlickmann, Michael G. Andreu, Caio Hamamura, Carine Klauberg, Carlos A. Silva

“…These findings highlight the importance of selecting segmentation algorithms based on specific research goals, balancing accuracy and computational feasibility in forest structural modeling.…”
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Navigating Ethical Dilemmas Of Generative AI In Medical Writing by Qurrat Ulain Hamdan, Waleed Umar, Mahnoor Hasan

“…Online resources like Wikipedia and WebMD, while mostly accurate, are generally not considered clinically or medically credible. …”
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A novel anthropometric method to accurately evaluate tissue deformation by Chongyang Ye, Xiaolu Li, Haiyan Song, Yu Shi, Ruixin Liang, Jun Zhang, Ka Po Lee, Zhaolong Chen, Beibei Zhou, Raymond Kai-Yu Tong, Kit-Lun Yick, Sun-Pui Ng, Joanne Yip

“…Moreover, a novel anthropometric method based on image recognition algorithms that systematically measures and evaluates tissue deformation while minimizing the impact of the effects of motion is proposed. …”
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Reverberation Mapping of Lamppost and Wind Structures in Accretion Thin Disks by James Hung-Hsu Chan, Joshua Fagin, Henry Best, Matthew J. O’Dowd

“…Our simulation approach rapidly generates quasar light curves while accommodating various observational scenarios for reverberation mapping, making it well-suited for training machine learning algorithms.…”
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Grassland management and phenology affect trait retrieval accuracy from remote sensing observations by Maksim Iakunin, Franziska Taubert, Reimund Goss, Severin Sasso, Hannes Feilhauer, Daniel Doktor

“…This study combines radiative transfer model (RTM) and machine learning algorithms to assess the efficacy of the model inversion in predicting plant functional traits under different grassland management regimes. …”
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Machine learning-based prediction model for recurrence after radiofrequency catheter ablation in patients with atrial fibrillation by Lujing Nie, Tianwei Zhang, Wenhua Wang, Xuefu Han, Meng Liu, Shujie Zhang, Wenjiu Feng, Yujie Wang, Yanbo Chen

“…Patients were randomly assigned to either a training cohort (70%) or a testing cohort (30%). Four ML algorithms were employed to develop prediction models. …”
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Revolutionizing total hip arthroplasty: The role of artificial intelligence and machine learning by Umile Giuseppe Longo, Sergio De Salvatore, Alice Piccolomini, Nathan Samuel Ullman, Giuseppe Salvatore, Margaux D'Hooghe, Maristella Saccomanno, Kristian Samuelsson, Rocco Papalia, Ayoosh Pareek

“…Abstract Purpose There has been substantial growth in the literature describing the effectiveness of artificial intelligence (AI) and machine learning (ML) applications in total hip arthroplasty (THA); these models have shown the potential to predict post‐operative outcomes using algorithmic analysis of acquired data and can ultimately optimize clinical decision‐making while reducing time, cost and complexity. …”
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Review of Demand Response-based Optimal Scheduling of Electric and Thermal Integrated Energy Systems by Jingshan MO, Guangxian YAN, Na SONG, Mingyang YUAN

“…With the changes in energy demand and structure, the integrated energy system faces a marked decline in flexibility adjustment capacity while meeting customer demand and securing energy supply. …”
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A dataset of annotated free comments on the sensory perception of madeleines for benchmarking text mining techniquesRecherche.Data.Gouv by Michel Visalli, Ronan Symoneaux, Cécile Mursic, Margaux Touret, Flore Lourtioux, Kipédène Coulibaly, Benjamin Mahieu

“…Consumers in the first group provided only words or short expressions, while those in the second group used complete sentences. …”
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UAV image analysis for detecting rice seedling gaps and gap effect on grain yield by Sanai Li, Yubin Yang, Jing Zhang, Lloyd T. (Ted) Wilson, Stanley Omar P.B. Samonte, Fugen Dou, Tanumoy Bera, Xin-Gen Zhou, Darlene Sanchez, Jing Wang

“…For instance, yield was predicted to decrease when gap fraction was above 4.5 % at 300°D > 10 °C, while even a smaller gap fraction (>0.5 %) led to yield reductions at 600°D. …”
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Optimization of PV parameters under varied environmental conditions: A hybrid secant–Newton-Raphson method by Brahim El Fahmi, Driss Saadaoui, Imade Choulli, Khalid Assalaou, Ismail Abazine, Mustapha Elyaqouti, El hanafi Arjdal, Mohammed Agdam, Yassine El aidi Idrissi

“…The Newton-Raphson technique is then applied to iteratively solve the I-V equation to finalize parameter estimation, while minimizing the root mean square error (RMSE) between modeled and measured data. …”
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Evaluation of the Characteristics of Short Acquisition Times Using the Clear Adaptive Low-Noise Method and Advanced Intelligent Clear-IQ Engine by Ryosuke Ogasawara, Akiko Irikawa, Yuya Watanabe, Tomoya Harada, Shota Hosokawa, Kazuya Koyama, Keisuke Tsuda, Toru Kimura, Koichi Okuda, Yasuyuki Takahashi

“…Images were reconstructed using three-dimensional ordinary Poisson ordered-subset expectation maximization (OSEM) with time of flight (TOF) and OSEM with TOF and point spread function modeling (PSF) algorithms, with OSEM iterations adjusted from 1 to 20 and CaLM applied under Mild, Standard, and Strong settings. …”
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Combining Local Electromagnetic Scattering and Global Structure Features for SAR Open Set Recognition by Qinjie Lin, Hao Sun, Yanjie Xu, Junyu Wang, Kefeng Ji, Gangyao Kuang

“…However, existing SAR ATR primarily rely on algorithms from the field of computer vision, many methods have not adequately considered the imaging sensitivity of SAR images. …”
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The 2024 revised clinical guidelines on the management of thyroid tumors by the Japan Association of Endocrine Surgery by Iwao Sugitani, Naomi Kiyota, Yasuhiro Ito, Naoyoshi Onoda, Tomo Hiromasa, Kiyomi Horiuchi, Seigo Kinuya, Tetsuo Kondo, Sueyoshi Moritani, Kiminori Sugino, Hisato Hara

“…Based on these, we illustrated overall flows of care as “Clinical algorithms”. Necessary background knowledge of diseases and established clinical procedures for understanding the recommendations are presented in “Notes”, while information that may be clinically useful but for which evidence remains insufficient is included in “Columns”, based on the current state of evidence. …”
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Robust Semantic Segmentation of Wafer Transmission Electron Microscopy Image Using Multi-Task Learning With Edge Detection by Yongwon Jo, Jinsoo Bae, Hansam Cho, Sungsu Kim, Heejoong Roh, Kyunghye Kim, Munki Jo, Munuk Kim, Jaeung Tae, Seoung Bum Kim

“…However, the automated measurement of wafer TEM images presents three main challenges: difficulty in image acquisition, significant noise, and ambiguous object boundaries. While existing methods for automated measurement have used semantic segmentation algorithms, they often lead to inaccurate object boundary detection, resulting in over- or under-estimation. …”
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Battery Energy Storage Systems in Microgrids: A Review of SoC Balancing and Perspectives by Thales Augusto Fagundes, Guilherme Henrique Favaro Fuzato, Lucas Jonys Ribeiro Silva, Augusto Matheus dos Santos Alonso, Juan C. Vasquez, Josep M. Guerrero, Ricardo Quadros Machado

“…In addition, this article explores optimization processes aimed at reducing operational costs while considering SoC equalization. Finally, second-life BESS units are explored as an emerging topic, focusing on their operation within specific power converters topologies to achieve SoC balance.…”
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A multimodal approach for enhanced disease management in cauliflower crops: integration of spectral sensors, machine learning models and targeted spraying technology by Rohit ANAND, Roaf Ahmad PARRAY, Indra MANI, Tapan Kumar KHURA, Harilal KUSHWAHA, Brij Bihari SHARMA, Susheel SARKAR, Samarth GODARA, Shideh MOJERLOU, Hasan MIRZAKHANINAFCHI

“…The decision tree model achieved 89.9% testing accuracy, while the SVM model achieved 96.7% accuracy using hyperparameters: cost of 10.0 and tolerance of 0.001. …”
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Hyperparameter optimisation in deep learning from ensemble methods: applications to proton structure by Juan Cruz-Martinez, Aron Jansen, Gijs van Oord, Tanjona R Rabemananjara, Carlos M R Rocha, Juan Rojo, Roy Stegeman

“…These hyperparameters must be determined separately from the model parameters such as network weights, and are often fixed by ad-hoc methods or by manual inspection of the results. An algorithmic, objective determination of hyperparameters demands the introduction of dedicated target metrics, different from those adopted for the model training. …”
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Comparison of in Situ Plant Area Index and Remotely Sensed Leaf Area Index of Northeastern American Deciduous, Mixed, and Coniferous Forests for SMAPVEX19-22 by Christopher L. Cook, Laura Bourgeau-Chavez, Dorthea Vander Bilt, Mary Ellen Miller, Simon Kraatz, Michael H. Cosh, Victoria R. Kelly, Andreas Colliander

“…We also discuss considerations for the LAI algorithms. The higher resolution RS products showed a consistently low bias (by ∼1 unit) in both spring and summer compared to in situ PAI measurements, while the coarse resolution LAI products matched in situ PAI values in spring but overestimated LAI by ∼ 1 unit in the summer. …”
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A secure and efficient user selection scheme in vehicular crowdsensing by Min Zhang, Qing Ye, Zhimin Yuan, Kaihuan Deng

“…To protect user privacy, pseudonyms are generated to achieve user anonymity while ensuring traceability. In addition, a prediction model based on principal component analysis-enhanced long short-term memory (PCA-Enhanced LSTM) model is constructed by combining the advantages of principal component analysis (PCA) and long short-term memory (LSTM) network. …”
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